Translator Disclaimer
September 2018 Modelling and Computation Using NCoRM Mixtures for Density Regression
Jim Griffin, Fabrizio Leisen
Bayesian Anal. 13(3): 897-916 (September 2018). DOI: 10.1214/17-BA1072

Abstract

Normalized compound random measures are flexible nonparametric priors for related distributions. We consider building general nonparametric regression models using normalized compound random measure mixture models. Posterior inference is made using a novel pseudo-marginal Metropolis-Hastings sampler for normalized compound random measure mixture models. The algorithm makes use of a new general approach to the unbiased estimation of Laplace functionals of compound random measures (which includes completely random measures as a special case). The approach is illustrated on problems of density regression.

Citation

Download Citation

Jim Griffin. Fabrizio Leisen. "Modelling and Computation Using NCoRM Mixtures for Density Regression." Bayesian Anal. 13 (3) 897 - 916, September 2018. https://doi.org/10.1214/17-BA1072

Information

Published: September 2018
First available in Project Euclid: 26 October 2017

zbMATH: 06989972
MathSciNet: MR3807871
Digital Object Identifier: 10.1214/17-BA1072

JOURNAL ARTICLE
20 PAGES


SHARE
Vol.13 • No. 3 • September 2018
Back to Top